A short, practical introductory course from Kaggle covering core machine learning concepts and how to apply them with scikit-learn in Python. Commenters describe it as very short and hands-on.

Commenters call it a quick, practical starting point that gets you practicing machine learning in Python, and suggest following it with Andrew Ng's course for more rigor.

On Reddit (2)

1. RecommendsCassegrain07r/learnmachinelearning2021in “Need Resources for Machine Learning Internship interview”▲ 1

   Do you have some background in this topic? What do you know about coding in python? I mean, are you familiar with lists and dictionaries? Do you know how to use scikit-learn library in order to implement ML algorithms (such as linear regression)? Regarding python I would recommend this course from…

2. RecommendsCodda-r/learnprogramming2020in “Where to learn the math for data science?”▲ 1

   You can do Kaggle's course Intro to machine learning and intermediate machine learning. It will be enough to **start practicing** on lower-end kaggle competitions. Then, if you want to be serious about Machine Learning in the long run, I suggest you to get very good fundation in calculus…

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